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Fuzzy Sketch for Implementation of E-Business Plan in Iran SMEs (Case Study: Yazd Industrial Town-Iran) Yasser Amiri Executive Master of Business Administration (EMBA), University of Yazd, Iran E-mail:
[email protected] Dr. Habibollah Salarzehi Faculty of Management and Accounting, University of Sistan and Baluchestan, Iran E-mail:
[email protected] Abstract Significant developments in IT and communications systems in the world specifically in recent decades have prompted under-developed countries to become sensitive to new opportunities and undertake an all-out planning to register a jump in their development and increase their economic and social growth in a bid to narrow their gap with developed countries and even vie with them. To that effect, e-commerce has been lent too much credence and our study here seeks to analyze the elements required for implementing e-business plans in small and medium-sized enterprises. To this end, we present a fuzzy map-based methodology in order to explore the most important critical success or failure factors for implementing e-business plan. Conducting an analysis on 61 indices bring us to the conclusion that factors like development, education and management of human resources, production scheduling, foreign relations management, communications systems and financial management are among the important critical failure factors. Keywords: E-commerce, E-business plan, Critical success and failure factors, Fuzzy logic, SMEs 1. Introduction Today, the Information Technology has caused numerous developments in commerce. These developments are not due to the facility or rapid growth of IT and the main reason behind the daily-increasing use of IT and Internet is the ability to cross international frontiers and exchange data regardless of geographical restrictions (Hayak, 2002). E-business is one of the IT and communications sectors to have been widely experienced in the past decade. Most enterprises are implementing e-business plan in an attempt to win a toehold in global markets and win over new, influential and effective customers. But using e-business plan in commercial activities requires attention to a series of influential endogenous and exogenous factors. The enterprises' heed to these factors and planning to make the best use of e-business technology will guarantee their success and help them grow (Gharbali Moqaddam and Eqdami, 2003). All pieces of research conducted hitherto about e-business have pointed only to specific aspects of the relevant factors. But in our research, we are determined to study the research activities carried out so far in order to indentify all relevant factors in view of finding out the most important critical success and failure factors in implementation of e-business plan in small and medium-sized enterprises. Since in our research, we cite views of experts and interviews in a qualitative manner, assessment of the views of the sample space by non-fuzzy methods could be called into question for two reasons. The first and foremost is that non-fuzzy methods ignore the ambiguity related to individual judgments when figures are transferred. The second point is that mental judgment, choice and priority of assessors largely impact the results (Ching et al, 2005). But fuzzy methods serve as helpful tool for handling vague problems. Fuzzy concepts can help us use linguistic variables in naturally colloquial langue for assessment of indices and present more precise analyses by connecting these variables with proper membership functions. This article seeks to implement a fuzzy approach to examine the factors contributing to the implementation of e-business plan. 2. Literature review Small businesses play an important role in economies all over the world by creating jobs and contributing to the socio-economic development of their communities. Small business owners possess little or no training on ITs and lack awareness of the benefits that ITs may provide to their business. The result is a major barrier to IT
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adoption. The smaller the enterprise, the greater that this problem becomes, since most small companies are not using IT for their business activities (Wolcott, 2008). Electronic business is defined as doing business through automatic transactions, exchanges and interactions by information and communications technologies in view of economic objectives. E-business may include inter-organizational systems like telephone, Internet, email or intranet to support online commerce. Therefore, one can say that e-business requires automatic transactions in business (Hanafizadeh, 2006) Depending on whether organizations or individuals are the adversary party, e-business could be classified as follows. Relationships take shape based on commercial objectives. Business to Business (B2B) Business to Consumer (B2C) Consumer to Consumer (C2C) Business to Government (B2G) Government to Business (G2B) E-business plan in different markets requires knowledge about the obstacles on the way of implementing this technology in the economy of each country (with regards to cultural, social, political and economic differences) specifically in their financial markets. Numerous studies have been conducted about these obstacles and we refer to them in short. Akkerenand and Cavaye (2002) have divided the factors influencing electronic commerce into three groups: 1) The features of manager and owner (perceived interests, computer knowledge, self-confidence, perceived control, mental norms) 2) Investment efficiency rate 3) Features of the organization (readiness, external pressure, complexity of structure, information intensity) Flynn and Purchase (2001) have their own classification of barriers: 1) Technical barriers: encoding, lack of qualified staff, low-speed Internet, compatibility to different systems 2) Financial barriers: Inability to reach the proper output, high-risk investment, costly training of staff, lack of productivity and mistrust of the market, available credit, high implementation costs 3) Organizational barriers: Lack of commerce models, weak programming and organization, lack of enough knowledge, lack of infrastructure, resistance of trade partners, implementation scheduling, lack of interest in EC 4) Behavioral barriers: Confidence and risk, cheating, resistance to any change in the current processes, need for new training courses Mukti (2000) examined the barriers to implementation of EC and expressed them in terms of significance as follows: security, financial and contractual barriers, hackers intervention, lack of skilful IT staff, Internet phishing, lack of globalization activities, confidentiality, ownership, insufficient computers and Inquisition. In developing countries, extensive Internet restrictions could be attributed to the market and infrastructural factors controlling access to ICTs (Mercer, 2006). Moreover, producers of ICT products have found leading distributors often in developed countries thereby limiting the access to developing countries. Lack of access to credit cards is a main barrier to e-business development. Previous studies have reached that conclusion in B2C electronic commerce in Russia, India and Latin America. In Asia, between 35 and 40 percent of exchanges are carried out in cash (face-to-face) (Biederman, 2002). Other aspects of financial systems have also lagged behind standards and they have failed to progress as they merit. For instance in the Caribbean islands, banks offer no online exchanges or electronic payment. Political barriers are created in an organized way by official groups. Many developing countries lack any regulations to recognize and certify digital and electronic signature. Some developing countries regard ICT products as luxury materials and they levy customs duties, value-added tax and extra commercial rights on them (UNCTAD, 2002). For their part, weak official organs contribute to lowering the customer's confidence in EC and their inclination for online purchase.
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A relevant study conducted in Brazil attributes the low rate of incompatibility with EC to the lack of any EC regulations, insufficient support for Internet purchases, concerns about privacy and confidentiality and Internet taxation (Tigre and Dedrick, 2004). In developing countries, the organization's staff, the nature of the activity, technological resources, lack of knowledge about potential opportunities, incompatibility with new phenomena and inclination for inertia result in a negative impression about EC (Molla and Licker, 2005). The lack of knowledge among customers about the advantages of EC and their mistrust of the electronic service providers also hinder any development of EC in these countries. For instance, the low level of tendency to use credit cards in Latin America is attributed to their mistrust of service providers rather than to their limited access (Hilbert, 2001). Another study showed that confidence in post networks for a 100-dollar package is strongly compatible with GNP per capita (the purchasing power factor). Also, concerns related to post robberies hamper EC in Tanzania (Kshetr, 2007). A total of 61 indices identified through the literature of the research works already done classified within ten criteria. The elements and factors used in this research are illustrated in Table 1(Ozer, 2002; Kendall, 2001; Cooper, 1999; Grandon & Pearson, 2004; Ling, 2001; Rashid & Qirim, 2001; Wang & Tsai, 2002; Heck & Ribbers, 1999; Daniel & Gkimshaw, 2002; Molla & Licker, 2001; Quaddus & Didi , 2005). 3. Methodology In this study, we intend to work out a methodology for elucidation of fuzzy sketch and identification of critical success and failure factors in implementation of e-business plan in SMEs by using fuzzy assessment principles. 3.1. Sample A total of 130 managers and experts from small and medium-sized enterprises active in the Yazd industrial town participated in the study. 3.2. Designing the research questionnaire A questionnaire based on the factors presented in table 1 has been designed and distributed among participants in question to measure the performance and significance of factors of e-business plan implementation in SMEs. Some variables like the sector in which the firms have been active and duration of the firm’s life have been control variables and haven’t had effect on the other variables. The vagueness and uncertainty arising in human evaluation of these indices makes the conclusion inaccurate and imprecise, but the fuzzy logic takes into account the vagueness and uncertainty and offers a proper tool for dealing with them. The linguistic variables and fuzzy numbers used in this research have been proposed in Table 2. 3.3. Validity & Reliability of research tool In order to endorse the content and criterion validity, the university professors and experts were asked to express themselves about the items of each factor using the following terms: absolutely appropriate, appropriate, somewhat appropriate, inappropriate and absolutely inappropriate. Once the views collected, the validity of the questionnaire of our research was estimated at 0.894. The Cronbach's alpha has been calculated in order to confirm the reliability of the questionnaire. It has been computed at 0.970. The alpha calculated for each factor is above 0.70, showing the acceptability of the reliability of the questionnaire. 3.4. Integration of views Many methods like average, median and mode could be used for integrating the evaluations of different decision-makers. Average has largely been used in different pieces of research and here we use it again. Assume the assessment committee is comprised of m assessors, E t , t 1, 2, ..., m and the elements of e-business are indicated with F j , j 1, 2, ..., n . Moreover, suppose that there are Rtj ( a jt , b jt , c jt ) and Wtj ( x jt , y jt , z jt ) fuzzy numbers used for estimating linguistic phrases to show the performance and importance of each element respectively. The following formulas show how the fuzzy ranking mean R j and the weighted fuzzy mean W calculated.
j
are
Formula 1: R j (a j , b j , c j ) (R j1 () R j 2 ()...() R jm / m. Formula 2: Wj (x j , y j , z j ) (Wj1()Wj 2 ()...()Wjm / m. 174
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The fuzzy numbers corresponding to the linguistic evaluations of the elements have been illustrated in Table 3 in the Appendix. 3.5. Locating items on the fuzzy sketch of e-business plan implementation SMEs The vertical pivot describes the performance and the horizontal one describes the significance of the factors of implementing e-business plan in SMEs. The data are finalized and each pivot is divided into three segments to give nine geographical locations. Each item will be located in a unique position based on the score it has obtained in the preceding step. Like a geographical map, this map will locate the items of implementation of e-business plan. The locations on the diameter of the matrix show the balance between the significance and performance. The factors lying there enjoy relative balance because the scores are mean. Three locations above the diameter show defection and fault due to the fact that their performance has not been heeded despite the high importance of elements. And the three locations beneath the diameter indicate the elements with overwork compared to their significance. Based on the data provided in Table 3 of Appendix, the fuzzy sketch is like Figure 1. 3.6. Ranking critical success and failure factors in e-business plan implementation The faulty factors are in fact barrier hindering the implementation of e-business plan in SMEs and they are considered to be critical failure factors. Similarly, the factors located beneath are critical success factors. Since it is impossible to concentrate on all of these factors, they need to be ranked and then the most important and most influential of them would be identified by Pareto Law. 3.6.1. Weighted Performance of Factors of E-Business Plan Implementation in SMEs Considering the significance of factors and their performance together can promote the ability to elucidate the success or failure indicator. Based on this interpretation, the factors with higher degree of significance and performance get higher scores. The significance is multiplied by the performance to produce a fuzzy number for ranking. And for critical failure factors ranking, the important point is that harmful factors are those with lower performance, regardless of their high significance. In order to obtain an indicator to measure the critical degree of these factors, the significance has first to be inversed before being multiplied by performance. The resultant in a progressive form will be indicative of the harmfulness of factors. Suppose W j , R j , j 1,2,..., n are fuzzy performance and fuzzy significance given to the item (j) and we are in the critical success factors area. The fuzzy numbers indicative of the final significance of these factors in success are calculated as follows: n
Formula 3: CSFS (W 0R ) j j j 1 On the other hand, in case the aforementioned scores belong to critical failure factors, the fuzzy numbers are calculated as follows: n
Formula 4: CFFS ((1 W )0R ) j j j 1 The critical success and failure factors have been ranked in Tables 4 and 5 in the Appendix. 3.6.2 Most influential critical success and failure factors in e-business plan implementation In this stage, the scores from the previous stage are ranked in order to clarify their significance to senior managers and decision-makers. The 5th column of Table 4 and 5 of Appendix(Index column) show the priority for fuzzy numbers. Since taking into consideration a large number of variables in a short period of time is impossible, it would be necessary to determine the most influential ones. Pareto Law can help us achieve this objective. According to this law, 80 percent of effects are due to 20 percent of causes. Based on this principle, paying attention to this 20 percent could influence 80 percent of effects. The 6th and 7th columns of Tables 4 and 5 in the Appendix show the relevant calculations. According to Table 4 and 5, the most critical failure factors are as follows: Development, education and management of human resources Production scheduling Foreign relations management Upgraded communications systems Generation and management of finance
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And the most important critical success factors are: Price of commodities or services Performance of customers International relations 4. Conclusion This research has been conduced to provide the grounds for implementing e-business plan in small and medium-sized enterprises. To that effect, the literature of the research and feedback of views of experts helped identify 61 elements within the framework of ten factors. The conclusion from fuzzy set was that the most important critical failure factors in the e-business plan included development, education and management of human resources, production scheduling, management of foreign relations, upgraded communications systems in the organization as well as generation and management of funds. The following points could be taken into account for improving the implementation job. (1) Long-term planning to remove barriers to e-business and e-commerce (2) Reconsidering the processes in small and medium-sized enterprises in order to serve customers based on competitive advantages due to IT and communications technology (3) Convincing managers about their tasks vis-à-vis e-business plan (4) Training the staff about new skills about e-business (5) Regular investment in IT and communications to boost the security of electronic networks (6) Employing prominent experts and qualified managers (7) Management stability, reduced purge among decision-makers and setting a scheduling for e-business implementation References Akkeren, J. K. V and Cavaye, A. L. M. (2000). “Factors Influence on Entry-level Electronic Commerce Adoption in the Automobile Industry in Australia”, Working Paper. Biederman, D. (2000). “Ecommerce comes to Asia”, Traffic World 26 (9) 23. Ching-Torng, L. Hero, Ch. Po-Young, Ch. .(2005). “Agility index in the supply chain”, Int. J. Production Economics.34, Pp. 141-159 Cooper, J. and Burgess, L. (1999) “A model of Internet commerce adoption (MICA)”, Idea Group Publishing, p.210. Daniel, E.M. and Gkimshaw, D.J. (2002) “An exploratory comparison of electronic commerce adoption in large and small enterprises”, Journal of Technology, Vol. 17, pp. 133-147. Flynn, A. and Purchase, S. (2001). “Perceptions of Barriers to E-Commerce”, ANZMAC Conference, 1st-5th December, Massey University, New Zealand. Garbali Moqaddam and Eqdami (2003), “e-business, a requirement to global trade”, Tadbir, 141. Grandon, Elizabeth and Pearson, M. (2004)”Electronic commerce adoption: an empirical study of small and medium US businesses”, Information & Management, 42, pp. 197-216. Hanafizadeh, P. (2006). “E-commerce, definitions and barriers, Sharif university”, Tehran, Iran. Hayak, V. (2002). “Economics and knowledge”, Economical N41, www.virtualschool.Edui/ Economicsandknowledge.Html. Heck, E.V. and Ribbers, P.M. (1999).”The adoption and impact of EDI in Dutch firms”, Proceedings of the 32nd Hawaii International Conference on System Science, pp.157-172. Hilbert, M.(2001). “Latin America on its Path into the Digital Age: Where are we? “CEPAL/ECLAC, Santiago, Chile. Kendall, Jon (2001).”Receptivity of Singapore”s SMEs to electronic commerce adoption”, Journal of Strategic Information System, 10, pp. 223-242. Kshetr,N. (2007). “Barriers to e-commerce and competitive business models in developing countries: A case study”, Electronic Commerce Research and Applications 6 . 443–452. Ling, C. (2001).”Model of factor influences on electronic commerce adoption diffusion”, Curtin University of Technology, Working Paper, pp.10-16 Mercer, C. (2006). “Telecentres and transformations: modernizing Tanzania through the Internet”, African Affairs 105, 243–264. Molla, A. and Licker, P.S. (2005). “Perceived e-readiness factors in ecommerce adoption: an empirical investigation in a developing country”, International Journal of Electronic Commerce 10 (1) pp.83–110.
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Molla, A.and Licker, P.S. (2001).E-commerce systems success: An attempt to extend the Delone and Maclean Model of IS success, Journal of Electronic Commerce Research, Vol. 2, No.2, pp. 131-141. Mukti, N. A. (2000). “Barriers to putting business on Internet in Malaysia”, The Electronic Journal of Information System in Developing Countries, 2 (6), pp.1-6. Ozer, Muammer. (2002). "Online business: tailoring your business environment in order to compete", International Journal of Information Management, No.14, pp.35-49. Quaddus, Mohammed and Didi, Achjari. (2005). "A model for electronic commerce success" Telecommunications Policy, No. 29 , pp. 127-152 Rashid, M.A. and Qirim, N.A. (2001) "Ecommerce technology adoption framework by New Zealand SME’s", Research Letter of Information and Mathematical Science, Vol 2, pp. 63-70. Tigre, P.S. and Dedrick, J. (2004). “E-commerce in Brazil: local adaptation of a global technology, Electronic Markets” 14 (1) pp. 36–47. UNCTAD, (2000). “Building Confidence: Electronic Commerce and Development”, United Nations Conference on Trade and Development, Geneva. Wang, J. C. and Tsai, K.H. (2002) " Factors in Taiwanese firm’s decision to adopt electronic commerce: An empirical study", The World Economy, Vo. l25, November & August, pp. 1145-1167. Wolcott, P., Mehruz Kamal, M. and Qureshi, S. (2008), "Meeting the challenges of ICT adoption by micro-enterprises", Journal of Enterprise Information Management, Vol. 21 No. 6,616-632. Appendix Table 1. Factors of implementing e-business plan Items
Factor
Factor
Services to customers Management
Processing orders Supply Chain
Transportation system Production scheduling Inventory planning Sales and logistics Relations with vendors Good relations with customers Providing services to customers
Customer
Competitor s
Suppliers
Political & Law Infrastructur es
Monitoring market changes and customer satisfaction Performance of customers Making the organization agile and flexible Benchmarking models of successful rivals Innovation in marketing Winning foothold in markets where rivals are successful Conquering untapped markets where rivals are still absent Signing strategic contracts Price of commodities or services Quality (the ranking earlier agreed upon) On-time delivery Financial capability of supplier to make repay debts Geographical position of supplier Continued improvement of services or commodities Creativity Electronic contracts Electronic signature Guaranteed operation Intellectual property rights law Privacy Cybercrimes Supporting consumers Customs duties
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Technical Requirements
Financial Infrastructures
Organization Type Productions & Services
Items Development, education and management of human resources Management of information resources and systems Management of physical and financial resources Implementation of programs Management of improvement and change Management of foreign relations Acquisition, creation and management of finance Management of strategic projects Operation of informatics section and connection to Internet network Wireless communications Upgraded communications systems Systems analyzer presence Internet address (official website) Emergency power system for the network High security of the network International relations Secure E-payment Development of credit cards Development of banking network Organizational culture Size of the organization Contribution of senior managers Organizational structure Designing products and services Evaluating the effectiveness of new products/services Preparation for production Innovation development process and offering new products or services Output Innovation in the production process
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Table 2. Linguistic variable & Fuzzy numbers Linguistic variable
Value
Very Low Low Fairley Law Medium Fairley High High Very High
(0, 0. 5, 1.5) (1, 2, 3) (2, 3.5, 5) (3, 5, 7) (5, 6.5, 8) (7, 8, 9) (8.5, 9.5, 10)
Table 3. Fuzzy scores of importance and performance of items Item X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19 X20 X21 X22 X23 X24 X25 X26 X27 X28 X29 X30 X31 X32 X33 X34 X35 X36 X37 X38 X39 X40 X41 X42 X43 X44 X45
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Development, education and management of human resources Management of information resources and systems Management of physical and financial resources Implementation of programs Management of improvement and change Management of foreign relations Acquisition, creation and management of finance Management of strategic projects Operation of informatics section and connection to Internet network Wireless communications Upgraded communications systems Systems analyzer presence Internet address (official website) Emergency power system for the network High security of the network International relations Secure E-payment Development of credit cards Development of banking network Organizational culture Size of the organization Contribution of senior managers Organizational structure Designing products and services Evaluating the effectiveness of new products/services Preparation for production Innovation development process and offering new products/services Output Innovation in the production process Services to customers Processing orders Transportation system Production scheduling Inventory planning Sales and logistics Relations with vendors Good relations with customers Providing services to customers Monitoring market changes and customer satisfaction Performance of customers Making the organization agile and flexible Benchmarking models of successful rivals Innovation in marketing Winning foothold in markets where rivals are successful Conquering untapped markets where rivals are still absent
Importance
Performance
(8.43,9.28,7.36) (6.98,8.07,9.04) (6.60,7.76,8.82) (6.85,7.98,8.82) (7.73,7.94,8.96) (7.05,8.15,9.08) (4.06,8.15,9.08) (6.48,7.69,8.79) (6.55,7.75,8.82) (6.45,6.73,8.73) (7.03,8.11,9.05) (6.35,7.60,8.73) (7.43,8.49,9.32) (6.74,7.88,8.88) (6.76,7.94,8.96) (5.55,7.59,8.39) (6.47,7.66,8.75) (6.62,7.80,8.85) (6.04,7.26,8.41) (6.49,7.67,8.72) (6.47,7.72,8.80) (6.47,7.70,8.79) (6.13,7.37,8.54) (6.55,7.75,8.82) (6.32,7.56,8.71) (6.77,7.92,8.95) (6.48,7.66,8.74) (7.17,8.25,9.17) (7.05,8.15,9.08) (6.49,7.67,8.75) (6.52,7.71,8.81) (6.02,7.33,8.55) (6.82,7.97,8.98) (6.47,7.70,8.79) (6.57,7.74,8.83) (6.32,7.54,8.68) (6.15,7.42,8.61) (6.67,7.82,8.86) (6.77,7.92,8.95) (5.49,6.87,8.18) (6.21,7.48,8.64) (7.10,8.24,9.16) (7.03,8.11,9.05) (7.23,8.31,9.21) (6.37,7.62,8.72)
(3.20,4.82,6.44) (3.25,4.79,6.34) (3.80,5.42,7.03) (3.87,5.41,6.93) (3.34,4.86,6.41) (3.01,4.68,6.36) (3.37,4.89,6.45) (3.82,5.37,6.91) (3.15,4.79,6.45) (3.27,4.82,6.38) (3.23,4.69,6.16) (2.84,4.24,5.67) (4.39,5.89,7.39) (3.83,5.42,7) (3.30,4.93,6.57) (3.31,4.89,6.48) (3.30,4.77,6.23) (3.35,5,6.66) (3.02,4.51,6.01) (3.81,5.3,6.76) (3.10,4.59,6.10) (3.63,5.21,6.78) (3.50,5.16,6.81) (3.404.89,6.38) (3.34,4.95,6.57) (4.25,5.76,7.25) (3.12,4.64,6.17) (4.15,5.68,7.22) (3.49,5.10,6.73) (3.54,5.07,6.59) (4.00,5.55,7.08) (4.01,5.54,7.05) (2.83,4.23,5.69) (3.54,4.94,6.34) (3.90,5.48,7.03) (3.95,5.56,7.15) (3.42,5,6.57) (4.10,5.70,7.29) (3.49,5.09,6.68) (3.5,5.09,6.69) (3.34,4.88,6.42) (3.46,4.96,6.43) (3.27,4.87,6.48) (3.46,5.08,6.71) (3.72,5.31,6.91)
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X46 X47 X48 X49 X50 X51 X52 X53 X54 X55 X56 X57 X58 X59 X60 X61
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Signing strategic contracts Price of commodities or services Quality (the ranking earlier agreed upon) On-time delivery Financial capability of supplier to make repay debts Geographical position of supplier Continued improvement of services or commodities Creativity Electronic contracts Electronic signature Guaranteed operation Intellectual property rights law Privacy Cybercrimes Supporting consumers Customs duties
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(7.09,8.19,9.11) (5.59,6.98,8.30) (6.55,7.71,8.79) (6.99,8.10,9.05) (6.21,7.48,8.64) (6.65,7.82,8.85) (6.51,7.68,8.75) (6.82,7.96,8.95) (7.15,8.26,9.16) (6.95,8.07,9.03) (6.81,7.93,8.95) (6.97,8.12,9.08) (6.37,7.62,8.72) (6.97,8.09,9.05) (6.65,7.84,8.89) (7.06,8.17,9.10)
(3.90,5.47,7.04) (3.45,4.93,6.42) (3.35,4.87,6.39) (4.05,5.64,7.24) (3.87,5.40,6.92) (4.64,6.09,7.52) (4.25,5.80,7.33) (3.54,5.08,6.62) (3.41,4.98,6.53) (3.29,4.79,6.31) (3.31,4.95,6.59) (3.42,4.97,6.51) (3.53,5.15,6.78) (3.04,4.68,6.33) (4.05,5.65,7.23) (3.93,5.51,7.09)
Table4. Prioritizing critical failure factors Items
Importance
Performance
((1 W J )0 R j )
Index
Relative Importance
Accumulative Frequency
X1 X33 X6 X11 X7 X2 X29 X12 X21 X27 X4 X9 X17 X10 X14 X42 X43 X44 X53 X54 X55 X57 X59
(8.43,9.28,7.36) (6.82,7.97,8.98) (7.05,8.15,9.08) (7.03,8.11,9.05) (4.06,8.15,9.08) (6.98,8.07,9.04) (7.05,8.15,9.08) (6.35,7.60,8.73) (6.47,7.72,8.80) (6.48,7.66,8.74) (6.85,7.98,8.82) (6.55,7.75,8.82) (6.47,7.66,8.75) (6.45,6.73,8.73) (6.74,7.88,8.88) (7.10,8.24,9.16) (7.03,8.11,9.05) (7.23,8.31,9.21) (6.82,7.96,8.95) (7.15,8.26,9.16) (6.95,8.07,9.03) (6.97,8.12,9.08) (6.97,8.09,9.05)
(3.20,4.82,6.44) (2.83,4.23,5.69) (3.01,4.68,6.36) (3.23,4.69,6.16) (3.37,4.89,6.45) (3.25,4.79,6.34) (3.49,5.10,6.73) (2.84,4.24,5.67) (3.10,4.59,6.10) (3.12,4.64,6.17) (3.87,5.41,6.93) (3.15,4.79,6.45) (3.30,4.77,6.23) (3.27,4.82,6.38) (3.83,5.42,7) (3.46,4.96,6.43) (3.27,4.87,6.48) (3.46,5.08,6.71) (3.54,5.08,6.62) (3.41,4.98,6.53) (3.29,4.79,6.31) (3.42,4.97,6.51) (3.04,4.68,6.33)
(2.27,7.55,16.9) (2.87,8.56,18.0) (2.74,8.63,18.7) (3.05,8.83,18.2) (3.07,9.03,18.9) (3.10,9.24,19.1) (3.18,9.40,19.8) (3.48,10.0,20.7) (3.59,10.1,20.6) (3.43,10.1,21.2) (3.71,10.4,21.5) (3.93,10.8,21.7) (3.97,10.8,21.8) (3.72,10.7,22.2) (4.01,10.9,21.9) (4.10,11.1,22.0) (3.84,10.9,22.4) (4.26,11.3,22.3) (4.13,11.4,22.6) (4.25,11.4,22.7) (3.66,10.5,21.5) (4.51,12.2,24.3) (2.89,8.71,18.6)
0.556 0.551 0.550 0.550 0.548 0.548 0.546 0.543 0.542 0.541 0.541 0.541 0.540 0.539 0.539 0.539 0.539 0.539 0.539 0.539 0.539 0.539 0.539
0.045 0.044 0.044 0.044 0.044 0.044 0.044 0.044 0.043 0.043 0.043 0.043 0.043 0.043 0.043 0.043 0.043 0.043 0.043 0.043 0.043 0.043 0.043
0.045 0.089 0.133 0.177 0.221 0.264 0.308 0.352 0.395 0.438 0.482 0.525 0.568 0.612 0.655 0.698 0.741 0.784 0.827 0.871 0.914 0.957 1.000
Published by Canadian Center of Science and Education
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International Business Research
Table 5. Prioritizing critical success factors
Vol. 3, No. 4; October 2010
Items
Importance
Performance
W J 0 R j
Index
Relative Importance
Accumulative Frequency
X47 X40 X16 X23 X32 X36 X35 X31 X60 X52 X38 X26 X51
(5.59,6.98,8.30) (5.49,6.87,8.18) (5.55,7.59,8.39) (6.13,7.37,8.54) (6.02,7.33,8.55) (6.32,7.54,8.68) (6.57,7.74,8.83) (6.52,7.71,8.81) (6.65,7.84,8.89) (6.51,7.68,8.75) (6.67,7.82,8.86) (6.77,7.92,8.95) (6.65,7.82,8.85)
(3.45,4.93,6.42) (3.5,5.09,6.69) (3.31,4.89,6.48) (3.50,5.16,6.81) (4.01,5.54,7.05) (3.95,5.56,7.15) (3.90,5.48,7.03) (4.00,5.55,7.08) (4.05,5.65,7.23) (4.25,5.80,7.33) (4.10,5.70,7.29) (4.25,5.76,7.25) (4.64,6.09,7.52)
(5.48,14.8,28.3) (6.3,15.9,30.1) (5.32,11.7,28.7) (5.08,13.5,26.3) (5.80,14.7,28.0) (5.19,13.6,26.3) (4.56,12.3,24.0) (4.75,12.6,24.6) (4.47,12.1,24.2) (5.28,13.4,25.5) (4.66,12.4,24.2) (4.46,11.9,23.4) (5.30,13.2,25.1)
0.5140 0.5137 0.5136 0.5127 0.5120 0.5116 0.5115 0.5114 0.5111 0.5110 0.5110 0.5108 0.5103
0.0772 0.0772 0.0772 0.0770 0.0769 0.0769 0.0769 0.0768 0.0768 0.0768 0.0768 0.0768 0.0767
0.0772 0.1544 0.2316 0.3087 0.3856 0.4625 0.5393 0.6162 0.6930 0.7698 0.8466 0.9233 1.0000
Defection •X44
Defection •X1 •X54
•X42 •X7 •X43 •X57
High
•X6 •X11 •X59
•X2
Balanced •X28 •X46
•X61
•X29
•X49
•X53
•X4
•X55 •X33 •X26
•X5 •X15
•X39 •X56 •X18
•X3 •X24 •X48 •X8
•X9
Medium
Importance
•X14
•X21 •X27 •X12 •X17
•X34
•X20 •X10 •X58 •X45 Defection •X41 •X50
Low
•X22
•X51 •X35
•X38
•X31
•X52
•X30 Sufficiency •X36 •X25
Balanced
•X37
•X16 •X19 Balanced
•X60
•X47
•X23 Sufficiency
•X32 Overworked
•X40 •X13
Low
Medium Performance
High
Figure 1. The Fuzzy sketch of e-business plan implementation
180
ISSN 1913-9004
E-ISSN 1913-9012
